Time series

Seasonal adjustment

Seasonal adjustment or deseasonalization is a statistical method for removing the seasonal component of a time series. It is usually done when wanting to analyse the trend, and cyclical deviations from trend, of a time series independently of the seasonal components. Many economic phenomena have seasonal cycles, such as agricultural production, (crop yields fluctuate with the seasons) and consumer consumption (increased personal spending leading up to Christmas). It is necessary to adjust for this component in order to understand underlying trends in the economy, so official statistics are often adjusted to remove seasonal components. Typically, seasonally adjusted data is reported for unemployment rates to reveal the underlying trends and cycles in labor markets. (Wikipedia).

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Time Series Talk : What is Seasonality ?

Intro to seasonality in time series analysis

From playlist Time Series Analysis

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Time Series Talk : Seasonal ARIMA Model

Intro to the Seasonal ARIMA model in time series analysis.

From playlist Time Series Analysis

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Winter Is Coming…And So Is Seasonal Depression

Gloomy, cloudy days and the transition from summer to winter are dreaded by many for the same reason: shorter days with less sunlight. Internal body clocks known as circadian rhythms help us adjust our sleep and wakefulness accordingly. But for some, the disruption might lead to Seasonal

From playlist Original shorts

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17. Seasons and Climate

The Atmosphere, the Ocean and Environmental Change (GG 140) There are several factors that impact climate on Earth. Different areas on Earth have different climates depending on factors such as their latitude and surrounding terrain. Maps of annual average precipitation illustrate the

From playlist Atmosphere, Ocean and Environmental Change with Ron Smith

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18. Seasons and Climate Classification

The Atmosphere, the Ocean and Environmental Change (GG 140) The seasonal cycle on Earth causes shifts in the bands of precipitation in the northern and southern hemispheres. The polar front shifts between high and mid-latitudes which causes a latitudinal shift in the occurrence of fron

From playlist Atmosphere, Ocean and Environmental Change with Ron Smith

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Seasonal Teeth | Oddities

A pair of customers bring a new item to the table: handcrafted, toothy lockets! For more, visit http://science.discovery.com/tv/oddities/#mkcpgn=ytsci1

From playlist Oddities

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What causes the seasons?

There are a few persistent misconceptions about what causes the seasons. Most believe it is the distance between the Earth and sun which varies to give us seasonal temperature variations. However it is actually the directness of the sun's rays leading to more intense sunshine in summer and

From playlist Misconceptions

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Time Series in Mathematica

Gosia Konwerska discusses some of the tools for time series analysis in Mathematica in this presentation from the Wolfram Technology Conference. For more information about Mathematica, please visit: http://www.wolfram.com/mathematica

From playlist Wolfram Technology Conference 2012

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Astronomy - Ch. 9.1: Earth's Atmosphere (30 of 61) The Daily Warming Cycle: Part 2

Visit http://ilectureonline.com for more math and science lectures! In this video I will explain the daily warming cycle of Earth's atmosphere (Part 2) by calculating a typical example of the temperature increase in 1 hour. Next video in this series can be seen at: https://youtu.be/3yqwa

From playlist THE GREENHOUSE EFFECT

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Strata 2012: Hal Varian, "Using Google Data for Short-term Economic Forecasting"

Google Insights for Search provides an index of search activity for millions of queries. These queries can sometimes help understand consumer behavior. Hal describes some of the issues that arise in trying to use this data for short-term economic forecasts and provide examples. Hal Varian

From playlist Strata SC 2012

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Data Science - Part X - Time Series Forecasting

For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of Time Series forecasting techniques and the process of creating effective for

From playlist Data Science

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2.2.7 An Introduction to Linear Regression - Video 4: Linear Regression in R

MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Allison O'Hair Loading the datasets and using them in R. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu

From playlist MIT 15.071 The Analytics Edge, Spring 2017

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Rain and Native American Flutes - Relaxing Music

Rain sound and new age instrumental of native american flutes and nature sounds for relaxing, sleeping and meditation. Indian flute relaxing music.

From playlist Soothing Sounds

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Time Series Analysis for Business Statistics (part 1)

Moving from regression modeling, we add the variable of time to our model. By measuring data sequentially over multiple time periods, we are able to make predictions about what is likely to occur in the future. We explore time series and causal forecasting methods and identify four time se

From playlist Business Statistics Lectures (FA2020, QBA337 @ MSU)

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2.2.9 An Introduction to Linear Regression - Video 5: Understanding the Model

MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Allison O'Hair Determining whether to keep all the variables in your final model. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses a

From playlist MIT 15.071 The Analytics Edge, Spring 2017

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Introduction to Religion: Lecture 20 - Islam, Part 2

Investigates what religion is and does, compares religious ideas and practices, and explores how religion influences the relationship between individual and community. Learn more about Missouri State iCourses at http://outreach.missouristate.edu/icourses.htm

From playlist Missouri State: REL 100: Introduction to Religion | CosmoLearning Religious Studies

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Anomaly Detection : Time Series Talk

Detecting anomalies and adjusting for them in time series. Code used in this video: https://github.com/ritvikmath/Time-Series-Analysis/blob/master/Anomaly%20Detection.ipynb

From playlist Time Series Analysis

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Mountain Men: Eustace Makes a VALUABLE Trade (Season 11)

Eustace gathers supplies to teach his campers how to hunt, in this clip from Season 11, "Wheeling and Dealing." Love Mountain Men? Stay up to date on all of your favorite The HISTORY Channel shows at history.com/schedule. #MountainMen Subscribe for more from Mountain Men and other great

From playlist Mountain Men: Season 11 | New Episodes Thursdays at 10/9c | History

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Inflation data | Inflation | Finance & Capital Markets | Khan Academy

Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/economics-finance-domain/macroeconomics/macro-economic-indicators-and-the-business-cycle/macro-price-indices-and-inflation/v/inflation-data Looking at actual sequenti

From playlist Inflation - measuring the cost of living | Macroeconomics | Khan Academy

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Why The Shortest Day Of The Year Isn't The Coldest

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From playlist Society, Culture & Technology

Related pages

Phillips–Perron test | Seasonal year | Frisch–Waugh–Lovell theorem | Seasonally adjusted annual rate | TRAMO | Periodic sequence | Time series | Additive model | Official statistics | Unit root | R (programming language) | Demetra+ | Dummy variable (statistics) | Ergograph | EViews | Null hypothesis